| Attribute | Detail |
|---|---|
| Format | Online, self-paced course |
| Level | Basic / Beginner |
| Duration | 2–3 Weeks |
| Certification | e-Certification |
| Fee | ₹199 / $20 |
| Tools | Python Pandas Data Analysis Data Cleaning DataFrames |
About the Data Analysis with Pandas Course
The Data Analysis with Pandas course is a free, beginner-friendly self-paced program designed to help learners understand how to analyze and work with structured data using the Pandas library in Python.
The course introduces key concepts such as data loading, data cleaning, filtering, grouping, and basic analysis. Learners will explore how Pandas is used to handle datasets efficiently and generate meaningful insights. This course is ideal for beginners who want to start working with real data using Python.
Program Highlights
• Free beginner-level Pandas and data analysis course
• Online self-paced learning format
• Simple explanation of data manipulation concepts
• Covers data cleaning, filtering, and analysis basics
• Real-world examples using structured datasets
• Suitable for students and non-programmers
• e-Certification upon successful completion
Course Curriculum
Module 1: Introduction to Pandas and Data Analysis
- What is Pandas?
- Why Pandas is Used in Data Science
- Introduction to DataFrames and Series
- Applications of Data Analysis
Module 2: Working with Data in Pandas
- Loading Data from Files: CSV and Excel
- Understanding Rows and Columns
- Selecting and Filtering Data
- Basic Data Exploration
Module 3: Data Cleaning and Preparation
- Handling Missing Values
- Removing Duplicates
- Data Transformation Basics
- Preparing Data for Analysis
Module 4: Data Analysis Techniques
- Grouping and Aggregation
- Sorting and Summarizing Data
- Basic Statistical Analysis
- Identifying Trends and Patterns
Module 5: Applications and Next Steps
- Using Pandas in Real-World Projects
- Data Analysis in Business and Research
- Introduction to Visualization and ML
- Mini Learning Activity / Concept-Based Practice
Tools, Techniques, or Platforms Covered
Python Pandas Data Analysis Data Cleaning DataFrames
Real-World Applications
- Analyzing datasets for business insights
- Cleaning and preparing data for analysis
- Understanding trends and patterns in structured data
- Supporting research and academic projects
- Preparing for advanced data science and machine learning learning
Who Should Attend & Prerequisites
- This course is suitable for students, beginners, freshers, and professionals who want to learn data analysis using Python and Pandas.
- It is also useful for learners from engineering, computer science, business, statistics, research, and non-technical backgrounds interested in data.
Certification
